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Hans-Jörg Schulz

On Quality Indicators for Progressive Visual Analytics

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

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On Quality Indicators for Progressive Visual Analytics. / Angelini, Marco; May, Thorsten; Santucci, Giuseppe; Schulz, Hans-Jörg.

EuroVis Workshop on Visual Analytics (EuroVA). Eurographics Association, 2019. p. 25-29.

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

Harvard

Angelini, M, May, T, Santucci, G & Schulz, H-J 2019, On Quality Indicators for Progressive Visual Analytics. in EuroVis Workshop on Visual Analytics (EuroVA). Eurographics Association, pp. 25-29, International EuroVis Workshop on Visual Analytics, Porto, Portugal, 03/06/2019. https://doi.org/10.2312/eurova.20191120

APA

Angelini, M., May, T., Santucci, G., & Schulz, H-J. (2019). On Quality Indicators for Progressive Visual Analytics. In EuroVis Workshop on Visual Analytics (EuroVA) (pp. 25-29). Eurographics Association. https://doi.org/10.2312/eurova.20191120

CBE

Angelini M, May T, Santucci G, Schulz H-J. 2019. On Quality Indicators for Progressive Visual Analytics. In EuroVis Workshop on Visual Analytics (EuroVA). Eurographics Association. pp. 25-29. https://doi.org/10.2312/eurova.20191120

MLA

Angelini, Marco et al. "On Quality Indicators for Progressive Visual Analytics". EuroVis Workshop on Visual Analytics (EuroVA). Eurographics Association. 2019, 25-29. https://doi.org/10.2312/eurova.20191120

Vancouver

Angelini M, May T, Santucci G, Schulz H-J. On Quality Indicators for Progressive Visual Analytics. In EuroVis Workshop on Visual Analytics (EuroVA). Eurographics Association. 2019. p. 25-29 https://doi.org/10.2312/eurova.20191120

Author

Angelini, Marco ; May, Thorsten ; Santucci, Giuseppe ; Schulz, Hans-Jörg. / On Quality Indicators for Progressive Visual Analytics. EuroVis Workshop on Visual Analytics (EuroVA). Eurographics Association, 2019. pp. 25-29

Bibtex

@inproceedings{adcc0b5984e345dfb7c3947cabfbb807,
title = "On Quality Indicators for Progressive Visual Analytics",
abstract = "A key component in using Progressive Visual Analytics (PVA) is to be able to gauge the quality of intermediate analysis outcomes. This is necessary in order to decide whether a current partial outcome is already good enough to cut a long-running computation short and to proceed. To aid in this process, we propose ten fundamental quality indicators that can be computed and displayed to gain a better understanding of the progress of the progression and of the stability and certainty of an intermediate outcome. We further highlight the use of these fundamental indicators to derive other quality indicators, and we show how to apply the indicators in two use cases.",
author = "Marco Angelini and Thorsten May and Giuseppe Santucci and Hans-J{\"o}rg Schulz",
year = "2019",
doi = "10.2312/eurova.20191120",
language = "English",
isbn = "978-3-03868-087-1",
pages = "25--29",
booktitle = "EuroVis Workshop on Visual Analytics (EuroVA)",
publisher = "Eurographics Association",
note = "International EuroVis Workshop on Visual Analytics, EuroVA ; Conference date: 03-06-2019",
url = "https://www.eurova.org/eurova-2019",

}

RIS

TY - GEN

T1 - On Quality Indicators for Progressive Visual Analytics

AU - Angelini, Marco

AU - May, Thorsten

AU - Santucci, Giuseppe

AU - Schulz, Hans-Jörg

PY - 2019

Y1 - 2019

N2 - A key component in using Progressive Visual Analytics (PVA) is to be able to gauge the quality of intermediate analysis outcomes. This is necessary in order to decide whether a current partial outcome is already good enough to cut a long-running computation short and to proceed. To aid in this process, we propose ten fundamental quality indicators that can be computed and displayed to gain a better understanding of the progress of the progression and of the stability and certainty of an intermediate outcome. We further highlight the use of these fundamental indicators to derive other quality indicators, and we show how to apply the indicators in two use cases.

AB - A key component in using Progressive Visual Analytics (PVA) is to be able to gauge the quality of intermediate analysis outcomes. This is necessary in order to decide whether a current partial outcome is already good enough to cut a long-running computation short and to proceed. To aid in this process, we propose ten fundamental quality indicators that can be computed and displayed to gain a better understanding of the progress of the progression and of the stability and certainty of an intermediate outcome. We further highlight the use of these fundamental indicators to derive other quality indicators, and we show how to apply the indicators in two use cases.

U2 - 10.2312/eurova.20191120

DO - 10.2312/eurova.20191120

M3 - Article in proceedings

SN - 978-3-03868-087-1

SP - 25

EP - 29

BT - EuroVis Workshop on Visual Analytics (EuroVA)

PB - Eurographics Association

T2 - International EuroVis Workshop on Visual Analytics

Y2 - 3 June 2019

ER -